The week's pick
Reseach Article
Two Step Authentication for an Anomaly based Intrusion Detection System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 169 - Number 8 |
| Year of Publication: 2017 |
| Authors: Nikhil Vijaywar, Vivek Kumar and |
10.5120/ijca2017914849
|
Nikhil Vijaywar, Vivek Kumar and . Two Step Authentication for an Anomaly based Intrusion Detection System. International Journal of Computer Applications. 169, 8 ( Jul 2017), 36-39. DOI=10.5120/ijca2017914849
Abstract
Intrusion detection is an effective approach of dealing with problems in the area of network security. Rapid development in technology has raised the need for an effective intrusion detection system as the traditional intrusion detection method cannot compete against newly advanced intrusions. As most IDS try to perform their task in real time but their performance hinders as they undergo different level of analysis or their reaction to limit the damage of some intrusions by terminating the network connection, a real time is not always achieved. The system implements the detection algorithm as a Snort preprocessor component. Since they work together, a highly effective system against unknown threats (which was the main aim of the designed system.).
References
- L. J. G. Villalba, A. L. S. Orozco and J. M. Vidal. “Anomaly-Based Network Intrusion Detection System”, IEEE Latin America Transactions, Vol. 13, No. 3, March 2015
- Okane, Philip, et al. "Malware detection: program run length against detection rate." IET software 8.1 (2014): 42-51.
- Wu, B., Lu, T., Zheng, K., Zhang, D., & Lin, X. Smartphone “malware detection model based on artificial immune system”. China Communications, 11(13), 86-92.
- Uppal, D., Sinha, R., Mehra, V., & Jain, V. (2014, September). “Malware detection and classification based on extraction of API sequences” In Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on (pp. 2337-2342). IEEE.
- He, Daojing, Sammy Chan, and Mohsen Guizani. “Mobile application security: malware threats and defences” IEEE Wireless Communications 22.1 (2015): 138-144.
- D. Bolzoni, S. Etalle, P. Hartel, E. Zambon. POSEIDON : a 2- tier “Anomaly based network intrusion detection system”, IEEE april 2006.
- Artificial immune system based general purpose intrusion detection system. Technical report, January 2009.
- S. B. Medhdi, A. K. Tanwani, M. Farooq. IMAD: In execution malware analysis and detection. GECCO july 2009.
- J. Jung, V. Paxson, A. W. Berger, H. Balakrishnan “Fast portscan detection using sequential hypothesis testing”, IEEE may 2004.
- Y. Gu, A. McCallum, D. F. Towsley “Detecting anomalies in network traffic using maximum entropy estimation”, oct.2005.
- Garcia-Teodoro, Pedro, et al. "Anomaly-based network intrusion detection: Techniques, systems and challenges." computers & security 28.1 (2009): 18-28.
Index Terms
Keywords